According to one conventional fingerprint verification method for a security system, an image including the protuberant lines of a fingerprint is binarized and thinned so as to calculate a protuberant line pattern. Then branch points, end points and curvature are extracted from the protuberant line pattern as the main characteristics of the fingerprint. Based on those characteristics, a comparison is performed between a master image (image of a reference fingerprint) and a sample image (image of a fingerprint to be examined). Since in this prior art approach characteristics of interest appear over a relatively large portion of the entire fingerprint, it has been preferable in this conventional fingerprint verification method to evaluate a fingerprint image covering a wide area. Therefore, such images of fingerprints have been taken by rotating the finger, this including in the image not only the front part of the finger but also the sides of the finger.
The protuberant lines at the lower portion of the fingerprint, i.e., a joint part of a finger, are usually arranged in a horizontal direction; therefore, there are few characteristics. Furthermore, the image at the lower portion of the fingerprint is usually input incorrectly; therefore, it is ineffective data for fingerprint verification. Accordingly, when using such an image for fingerprint verification, accurate verification will be difficult to perform due to the vast volume of noise in the data. Also, when using raterized data representing the fingerprint, the volume of input data becomes so large that it becomes necessary to expand memory capacity, and comparison operations are complex and typically take a large amount of time to perform. The present invention vastly simplies these problems by implementing a vector analysis technique compatible with a much smaller image area of the fingerprint.